FitMyLLM
Alibaba/Dense

AlibabaQwen3 1.7B

Qwen3 1.7B — efficient small model with thinking/reasoning mode.

chatreasoningThinkingTool Use
2.03B
Parameters
32K
Context length
19
Benchmarks
6
Quantizations
300K
HF downloads
Architecture
Dense
Released
2025-04-28
Layers
28
KV Heads
8
Head Dim
128
Family
qwen

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
Q4_K_M4.89
3.0 GB
1.7 + 1.3 KV
good
Q5_K_S5.57
3.2 GB
1.9 + 1.3 KV
good
Q5_K_M5.7
3.2 GB
1.9 + 1.3 KV
good
Q6_K6.56
3.5 GB
2.2 + 1.3 KV
excellent
Q8_08.5
4.0 GB
2.6 + 1.3 KV
lossless
FP1616
5.9 GB
4.5 + 1.3 KV
lossless

Select your GPU above to see speed estimates and compatibility for each quantization.

Deploying for a team or in production? Size GPUs, cost & scaling in Enterprise →
READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN QWEN3 1.7B NOW

Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

Loading ratings...

Benchmarks (19)

MATH-50089.4
MATH72.0
HumanEval68.0
IFEval65.0
AIME38.7
AA Math38.7
GPQA Diamond35.6
LiveCodeBench30.8
BigCodeBench27.0
τ²-Bench21.6
IFBench21.1
MMLU-PRO19.8
BBH18.3
AA Intelligence8.0
SciCode6.9
HLE4.8
MUSR4.0
AA Coding1.4
GPQA0.0

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen3:1.7b-q4_K_M

Downloads and runs automatically. Add --verbose for speed stats.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

Find the best GPU for Qwen3 1.7B

Build Hardware for Qwen3 1.7B

Qwen3 1.7B — efficient small model with thinking/reasoning mode.

▸ SPEC SHEET

Qwen3 1.7B2.03B Dense.

▸ SPECIFICATIONS
PARAMETERS
2.03B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
32K tokens
CAPABILITIES
chat, reasoning
RELEASE DATE
2025-04-28
PROVIDER
Alibaba
FAMILY
qwen
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.891.7 GB94%
Q5_K_S5.571.9 GB96%
Q5_K_M5.71.9 GB96%
Q6_K6.562.2 GB97%
Q8_08.52.6 GB100%
FP16164.5 GB100%
§ 01BENCHMARK SCORES
HumanEval68.0
MMLU-PRO19.8
MATH72.0
IFEval65.0
BBH18.3
GPQA0.0
MUSR4.0
BigCodeBench27.0
GPQA Diamond35.6
LiveCodeBench30.8
AIME38.7
MATH-50089.4
HLE4.8
AA Intelligence8.0
AA Coding1.4
AA Math38.7
aa_ifbench21.1
aa_tau221.6
aa_scicode6.9
§ 02RUN COMMAND

Run Qwen3 1.7B locally with Ollama — needs 1.7 GB VRAM at Q4_K_M:

$ollama run qwen3:1.7b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M